VARYVARY

VaryVary is a 4-year research project funded by the French National Research Agency (ANR). The goal is to explore the use of artificial intelligence (including machine learning) for playing with software variability present in almost all real-world systems... In this project, we follow a thought-provoking and unexplored direction: We consider that the variability boundary of a software system can be specialized and should itself vary when needs be. The goal of this project is to provide theories, methods and techniques to make vary variability. Specifically, we consider machine learning and software engineering techniques for narrowing the space of possible configurations to a good approximation of those satisfying the needs of users. Based on an oracle (e.g., a runtime test) that tells us whether a given configuration meets the requirements (e.g. speed or memory footprint), we leverage machine learning to retrofit the acquired constraints into a variability model that can be used to..